@article{2249,
  author = {L. Wang, J. Shang},
  title = {Characters and Evaluation of P2P Botnet Node-based Detection},
  journal = {Journal of Information & Systems Management},
  year = {2017},
  volume = {7},
  number = {2},
  doi = {},
  url = {http://www.dline.info/jism/fulltext/v7n2/jismv7n2_1.pdf},
  abstract = {In this paper, we proposed a novel node-based P2P detection. Comparing to traditional server-client bonnet on the Internet, the P2P (peer-to-peer) 
bonnet has capabilities to realize highly scalable, extensible and efficient distributed applications. The node-based P2P detection exploits the node 
profile generated from the novel as well as the degradation of the amount of traffic handled with sampling. It is expected to grow the detection rate. 
With these commonality features, flow-based techniques can institute rules for multiple bonnets detection, as well as for some unknown bot nets. The 
disadvantage of this method is that some legitimate applications may share the same flow features. This could be expected to result in a high false 
positive rate. Node-based detection extracts more general features of a bonnet. One node represents one bot machine. This technique detects bonnets 
from a macroscopic angle. We hope that it would help people find useful information quickly.
},
}